• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.4
• /
• pp.203-209
• /
• 2023

Harmony search(HS) does not use the evaluation of individual harmony when referring to HM when constructing a new harmony, but particle swarm optimization(PSO), on the contrary, uses the evaluation value of individual particles and the evaluation value of the population to find a solution. However, in this study, we tried to improve the performance of the algorithm by finding and identifying similarities between HS and PSO and applying the particle improvement process of PSO to HS. To apply the PSO algorithm, the local best of individual particles and the global best of the swam are required. In this study, the process of HS improving the worst harmony in harmony memory(HM) was viewed as a process very similar to that of PSO. Therefore, the worst harmony of HM was regarded as the local best of a particle, and the best harmony was regarded as the global best of swam. In this way, the performance of the HS was improved by introducing the particle improvement process of the PSO into the HS harmony improvement process. The results of this study were confirmed by comparing examples of optimization values for various functions. As a result, it was found that the suggested HS-PSO was much better than the existing HS in terms of accuracy and consistency.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.5
• /
• pp.155-161
• /
• 2023

97.5% of our country's exports and 87.2% of imports are transported by sea, making ports an important component of the Korean economy. To efficiently operate these ports, it is necessary to improve the short-term prediction of port water volume through scientific research methods. Previous research has mainly focused on long-term prediction for large-scale infrastructure investment and has largely concentrated on container port water volume. In this study, short-term predictions for petroleum and liquefied gas cargo water volume were performed for Ulsan Port, one of the representative petroleum ports in Korea, and the prediction performance was confirmed using the deep learning model LSTM (Long Short Term Memory). The results of this study are expected to provide evidence for improving the efficiency of port operations by increasing the accuracy of demand predictions for petroleum and liquefied gas cargo water volume. Additionally, the possibility of using LSTM for predicting not only container port water volume but also petroleum and liquefied gas cargo water volume was confirmed, and it is expected to be applicable to future generalized studies through further research.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.2
• /
• pp.263-272
• /
• 2022

As a result of climate change, the heatwave and urban heat island phenomena have become more common, and the frequency of heatwaves is expected to increase by two to six times by the year 2050. In particular, the heat sensation index felt by workers at construction sites during a heatwave is very high, and the sensation index becomes even higher if the urban heat island phenomenon is considered. The construction site environment and the situations of construction workers vulnerable to heat are not improving, and it is now imperative to respond effectively to reduce such damage. In this study, satellite imagery, land surface temperatures (LST), and long short-term memory (LSTM) were applied to analyze areas above 33 ℃, with the most vulnerable areas with increased synergistic damage from heat waves and the urban heat island phenomena then predicted. It is expected that the prediction results will ensure the safety of construction workers and will serve as the basis for a construction site early-warning system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.5
• /
• pp.437-442
• /
• 2015

Recently, the size of point cloud is increasing rapidly with the high advancement of 3D terrestrial laser scanners. The study aimed for improving a file-referring octree, introduced in the preceding study, which had been intended to generate an octree and to query points from a large point cloud, gathered by 3D terrestrial laser scanners. To the end, every leaf node of the octree was designed to store only one file-pointer of its first point. Also, the point cloud file was re-constructed to store points sequentially, which belongs to a same leaf node. An octree was generated from a point cloud, composed of about 300 million points, while time was measured during querying proximate points within a given distance with series of points. Consequently, the present method performed better than the preceding one from every aspect of generating, storing and restoring octree, so as querying points and memorizing usage. In fact, the query speed increased by 2 times, and the memory efficiency by 4 times. Therefore, this method has explicitly improved from the preceding one. It also can be concluded in that an octree can be generated, as points can be queried from a huge point cloud, of which larger than the main memory.

• ALGAE
• /
• v.31 no.1
• /
• pp.73-84
• /
• 2016

Marine organisms are frequently used to be harmful and have lower side effects than synthetic drugs. The cognitive improving efficacy of gamma aminobutyric acid-enriched fermented Saccharina japonica (FSJ) on the memory deficient rats, which were induced by trimethyltin chloride (TMT), was investigated by assessing the Morris water maze test and by performing choline acetyltransferase (ChAT), cAMP response element binding protein (CREB), and brain derived neurotrophic factor (BDNF) immunohistochemistry. The neurite outgrowth of Neuro2a cells was assessed in order to examine the underlying mechanisms of the memory enhancing effects of FSJ. Treatment with FSJ tended to shorten the latency to find the platform in the acquisition test of the Morris water maze at the second and fourth day compared to the control group. In the probe trial, the FSJ treated group increased time spent in the target quadrant, compared to that of the control group. Consistent with the behavioral data, these treatments recovered the loss of ChAT, CREB, and BDNF immunepositive neurons in the hippocampus produced by TMT. Treatment with FSJ markedly stimulated neurite outgrowth of the Neuro2a cells as compared to that of the controls. These findings demonstrate that FSJ may be useful for improving the cognitive function via regulation of neurotrophic marker enzyme activity.

• Clinical and Experimental Pediatrics
• /
• v.60 no.11
• /
• pp.337-343
• /
• 2017

Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. This disorder, in addition to its main symptoms, creates significant difficulties in education, social performance, and personal relationships. Given the importance of rehabilitation for these patients to combat the above issues, the use of virtual reality (VR) technology is helpful. The aim of this study was to highlight the opportunities for VR in the rehabilitation of children with ADHD. This narrative review was conducted by searching for articles in scientific databases and e-Journals, using keywords including VR, children, and ADHD. Various studies have shown that VR capabilities in the rehabilitation of children with ADHD include providing flexibility in accordance with the patients' requirements; removing distractions and creating an effective and safe environment away from real-life dangers; saving time and money; increasing patients' incentives based on their interests; providing suitable tools to perform different behavioral tests and increase ecological validity; facilitating better understanding of individuals' cognitive deficits and improving them; helping therapists with accurate diagnosis, assessment, and rehabilitation; and improving working memory, executive function, and cognitive processes such as attention in these children. Rehabilitation of children with ADHD is based on behavior and physical patterns and is thus suitable for VR interventions. This technology, by simulating and providing a virtual environment for diagnosis, training, monitoring, assessment and treatment, is effective in providing optimal rehabilitation of children with ADHD.

• Journal of KIISE
• /
• v.43 no.9
• /
• pp.947-952
• /
• 2016

Most data centers attempt to consolidate servers using virtualization technology to efficiently utilize limited physical resources. Moreover, virtualized systems have commonly adopted contents-based page sharing mechanism for page deduplication among virtual machines (VMs). However, previous page sharing schemes are limited by the inability to effectively manage accumulated hints which mean sharable pages in stack. In this paper, we propose a priority-based hint management scheme to efficiently manage accumulated hints, which are sent from guest to host for improving page sharing opportunity in virtualized systems. Experimental results show that our scheme removes pages with low sharing potential, as compared with the previous schemes, by efficiently managing the accumulated pages.

• Biomolecules & Therapeutics
• /
• v.20 no.3
• /
• pp.332-339
• /
• 2012

The components of Magnolia officinalis have well known to act anti-inflammatory, anti-oxidative and neuroprotective activities. These efficacies have been sold many products as nutritional supplement extracted from bark of Magnolia officinalis. Thus, to assess and compare neuroprotective effect in the nutritional supplement (Magnolia $Extract^{TM}$, Health Freedom Nutrition LLC, USA) and our ethanol extract of Magnolia officinalis (BioLand LTD, Korea), we investigated memorial improving and anti-Alzheimer's disease effects of extract products of Magnolia officinalis in a transgenic AD mice model. Oral pretreatment of two extract products of Magnolia officinalis (10 mg/kg/day in 0.05% ethanol) into drinking water for 3 months ameliorated memorial dysfunction and prevented $A{\beta}$ accumulation in the brain of Tg2576 mice. In addition, extract products of Magnolia officinalis also decreased expression of ${\beta}$-site APP cleaving enzyme 1 (BACE1), amyloid precursor protein (APP) and its product, C99. Although both two extract products of Magnolia officinalis could show preventive effect of memorial dysfunction and $A{\beta}$ accumulation, our ethanol extract of Magnolia officinalis (BioLand LTD, Korea) could be more effective than Magnolia $Extract^{TM}$ (Health Freedom Nutrition LLC, USA). Therefore, our results showed that extract products of Magnolia officinalis were effective for prevention and treatment of AD through memorial improving and anti-amyloidogenic effects via down-regulating ${\beta}$-secretase activity, and neuroprotective efficacy of Magnolia extracts could be differed by cultivating area and manufacturing methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.3
• /
• pp.42-52
• /
• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• The Journal of the Korea Contents Association
• /
• v.15 no.7
• /
• pp.1-11
• /
• 2015

In recent high performance computing system, GPGPU has been widely used to process general-purpose applications as well as graphics applications, since GPU can provide optimized computational resources for massive parallel processing. Unfortunately, GPGPU doesn't exploit computational resources on GPU in executing general-purpose applications fully, because the applications cannot be optimized to GPU architecture. Therefore, we provide GPU research guideline to improve the performance of computing systems using GPGPU. To accomplish this, we analyze the negative factors on GPU performance. In this paper, in order to clearly classify the cause of the negative factors on GPU performance, GPU core status are defined into 5 status: fully active status, partial active status, idle status, memory stall status and GPU core stall status. All status except fully active status cause performance degradation. We evaluate the ratio of each GPU core status depending on the characteristics of benchmarks to find specific reasons which degrade the performance of GPU. According to our simulation results, partial active status, idle status, memory stall status and GPU core stall status are induced by computational resource underutilization problem, low parallelism, high memory requests, and structural hazard, respectively.